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# AidanGoth

Karma: 229
• Sorry for the slow reply. I don’t have a link to any examples I’m afraid but I just mean something like this:

Prior that we should put weights on arguments and considerations: 60%

Pros:

• Clarifies the writer’s perspective each of the considerations (65%)

• Allows for better discussion for reasons x, y, z… (75%)

Cons:

• Takes extra time (70%)

This is just an example I wrote down quickly, not actual views. But the idea is to state explicit probabilities so that we can see how they change with each consideration.

To see you can find the Bayes’ factors, note that if is our prior probability that we should give weights, is our prior that we shouldn’t, and and are the posteriors after argument 1, then the Bayes’ factor is

Similarly, the Bayes’ factor for the second pro is .

• Good questions! It’s a shame I don’t have good answers. I remember finding Spencer Greenberg’s framing helpful too but I’m not familiar with other useful practical framings, I’m afraid.

I suggested the Bayes’ factor because it seems like a natural choice of the strength/​weight of an argument but I don’t find it super easy to reason about usually.

The final suggestion I made will often be easier to do intuitively. You can just to state your prior at the start and then intuitively update it after each argument/​consideration, without any maths. I think this is something that you get a bit of a feel for with practice. I would guess that this would usually be better than trying to formally apply Bayes’ rule. (You could then work out your Bayes’ factor as it’s just a function of your prior and posterior but that doesn’t seem especially useful at this point/​it seems like too much effort for informal discussions.)

• Nice post! I like the general idea and agree that a norm like this could aid discussions and clarify reasoning. I have some thoughts that I hope can build on this.

I worry that the (1-5) scale might be too simple or misleading in many cases though and it doesn’t quite give us the most useful information. My first concern is that this looks like a cardinal scale (especially the way you calculate the output) but is it really the case that you should weigh arguments with score 2 twice as much as arguments with score 1 etc.? Some arguments might be much more than 5x more important than others, but that can’t be captured on the (1-5) scale.

Maybe this would work better as an ordinal ranking with 5 degrees of importance (the initial description sounds more like this). In the example, this would be sufficient to establish that the pros have more weight, but it wouldn’t always be conclusive (e.g. 5, 1 on the pro side and 4, 3 on the con side).

I think a natural cardinal alternative would be to give the Bayes’ factor for each alternative, and ideally give a prior probability at the start. Or similarly, give a prior and then update this after each argument/​consideration, so you and the reader can see how much each argument/​consideration affects your beliefs. I’ve seen this used before and found it helpful. And this seems to convey more important information than how important an argument/​consideration is: how much we update our beliefs in response to arguments/​considerations.

• I found this really motivating and inspiring. Thanks for writing. I’ve always found the “great opportunity” framing of altruism stretched and not very compelling but I find this subtle reframing really powerful. I think the difference for me is the emphasis on the suffering of the drowning man and his family, whereas “great opportunity” framings typically emphasise how great it would be for YOU to be a hero and do something great. I prefer the appeal to compassion over ego.

I usually think more along Singerian obligation lines and this has led to unhealthy “morality as taxes” thought patterns. On reflection, I realise that I haven’t always thought about altruism in this way and I actually used to think about it in a much more wholehearted way. Somehow, I largely lost that wholehearted thinking. This post has reminded me why I originally cared about altruism and morality and helped me revert to wholehearted thinking, which feels very uplifting and freeing. I plan on revisiting this whenever I notice myself slipping back into “morality as taxes” thought patterns.

• My reading of the post is quite different: This isn’t an argument that, morally, you ought to save the drowning man. The distant commotion thought experiment is designed to help you notice that it would be great if you had saved him and to make you genuinely want to have saved him. Applying this to real life, we can make sacrifices to help others because we genuinely/​wholeheartedly want to, not just because morality demands it of us. Maybe morality does demand it of us but that doesn’t matter because we want to do it anyway.

# Can we drive de­vel­op­ment at scale? An in­terim up­date on eco­nomic growth work

27 Oct 2020 11:14 UTC
89 points
14 comments20 min readEA link
• Yep, agreed!

• Great, sounds like you’re on top of all of this!

• Agreed. I didn’t mean to imply that totalism is the only view sensitive to the mortality-fertility relationship—just that the results could be fairly different on totalism and that it’s especially important to see the results on totalism and that it makes sense to look at totalism before other population ethical views not yet considered. Exploring other population ethical views would be good too!

If parents are trying to have a set number of children (survive to adulthood) then the effects of reducing mortality might not change the total number of future people much, because parents adjust fertility

I think my concern here was that the post suggested that saving lives might not be very valuable on totalism due to a high fertility adjustment:

A report writtenfor GiveWell estimated that in some areas where it recommends charities the number of births averted per life saved is as large as 1:1, a ratio at which population size and growth are left effectively unchanged by saving lives.[45] For totalists, the value of saving lives in a 1:1 context would be very small (compared to one where there was no fertility reduction) as the value of saving one life is ‘negated’ by the disvalue of causing one less life to be created.

Roodman’s report (if I recall correctly) suggested that this likely happens to a lower degree in areas where infant mortality is high (i.e. parents adjust fertility less in high infant mortality settings) so saving lives in these settings is plausibly still very valuable according to totalism.

• This is a great summary of what I was and wasn’t saying :)

Thanks for the link—looking forward to reading. Might return to this after reading

• You’re very welcome! I really enjoyed reading and commenting on the post :)

One thing I can’t quite get my head round—if we divide E(C) by E(L) then don’t we lose all the information about the uncertainty in each estimate? Are we able to say that the value of averting a death is somewhere between X and Y times that to doubling consumption (within 90% confidence)?

Good question, I’ve also wondered this and I’m not sure. In principle, I feel like something like the standard error of the mean (the standard deviation of the sample divided by the square root of the sample size) should be useful here. But applying it naively doesn’t seem to give plausible results because guesstimate uses 5000 samples, so we end up with very small standard errors. I don’t have a super strong stats background though—maybe someone who does can help you more here

• I wish this preference was more explicit in Founders Pledge’s writing. It seems like a substantial value judgment, almost an aesthetic preference, and one that is unintuitive to me!

We don’t say much about this because none of our conclusions depends on it but we’ll be sure to be more explicit about this if it’s decision-relevant. In the particular passage you’re interested in here, we were trying to get a sense of the broader SWB benefits of psychedelic use. We didn’t find strong evidence for positive effects on experiential or evaluative measures of SWB. As you rightly note, just using PANAS leaves open the possibility that life satisfaction could have increased (the former is an experiential measure and the latter is an evaluative one). But there wasn’t evidence for improvements in evaluative SWB either so that fact that we place more weight on experiential than evaluative measures didn’t play a role here.

The only time that we’ve used SWB measures to evaluate a funding opportunity, we looked at both happiness (an experiential measure) and life satisfaction (an evaluative measure).

I wonder which of hedonistic and preference utilitarianism you’re more sympathetic to, or which of hedonism and preference/​desire theories of well-being you’re more sympathetic to. The former tend to go with experiential SWB and the latter with evaluative or eudaimonic SWB (see Michael Plant’s recent paper). I don’t think it’s a perfect mapping but my inclination towards hedonism is closely related to my earlier claim that

experiential measures, such as affective balance (e.g. as measured by Positive and Negative Affect Schedule (PANAS)), capture more of what we care about and less of what we don’t care about, compared to evaluative measures, such as life satisfaction

This might explain our disagreement.

e.g. favoring affective balance over life satisfaction implies that having children is a bad decision in terms of one’s subjective well-being. (If I recall correctly, on average having kids tends to make affective balance go down but life satisfaction go up; many people seem very happy to have had children.)

This is an interesting example, thanks for bringing it up. I don’t have a strong view on whether having children increases or decreases hedonistic well-being (though it seems likely to increase well-being in desire/​preference terms). So I’m not too sure what to make of it but here are a few thoughts:

1. This could well be a case in which life satisfaction captures something important that affect and happiness miss—I don’t have a strong view on that.

2. The early years of parenting intuitively seem really hard and sleep-depriving but also fulfilling and satisfying in a broad sense. So it seems very plausible that they decrease affect/​happiness but increase life satisfaction. I’d expect children to be a source of positive happiness as well, later in life though, so maybe having children increases affect/​happiness overall anyway.

3. If having children decreases affect/​happiness, I don’t find it very surprising that lots of people want to have children and are satisfied by having children anyway. There are clearly strong evolutionary pressures to have strong preferences for having children but much less reason to think that having children would make people happier (arguably the reverse: having children results in parents having fewer resources for themselves!)

• Hi Milan, thanks very much for your comments (here and on drafts of the report)!

On 1, we don’t intend to claim that psychedelics don’t improve subjective well-being (SWB), just that the only study (we found) that measured SWB pre- and post-intervention found no effect. This is a (non-conclusive) reason to treat the findings that participants self-report improved well-being with some suspicion.

As I mentioned to you in our correspondence, we think that experiential measures, such as affective balance (e.g. as measured by Positive and Negative Affect Schedule (PANAS)), capture more of what we care about and less of what we don’t care about, compared to evaluative measures, such as life satisfaction. But I take your point that PANAS doesn’t encompass all of SWB.

On 2, behaviour change still hasn’t been studied enough for there to be more than “weak evidence” but yeah, I agree that reports from third-parties are stronger evidence than self-reported changes.

Also interesting here – individuals may rescale their assessments of subjective well-being over time. I speculate that the particulars of the psychedelic experience may drive rescaling like this in an intense way.

Yeah, I don’t think we understand this very well yet but it’s an interesting thought :)

• I’ve hopefully clarified this in my response to your first comment :)

• Thanks for your questions, Siebe!

Based on the report itself, my impression is that high-quality academic research into microdosing and into flow-through effects* of psychedelic use is much more funding-constrained. Have you considered those?

Yes, but only relatively briefly. You’re right that these kinds of research are more neglected than studies of mental health treatments but we think that the benefits are much smaller in expectation. That’s not to say that there couldn’t be large benefits from microdosing or flow-through effects, just that these are much more speculative.

Note that we think it’s more likely than not (59%) that psilocybin will turn out to be less effective than existing treatments for depression (pg. 35). Even the mental health benefits are fairly uncertain and these other benefits you mention are even less likely to materialise. The kinds of research you suggest could be valuable but I think it makes sense to focus on the mental health treatments first.

On microdosing specifically, we mention our specific concerns (pg. 21):

Another psychedelics intervention that is often suggested as potentially promising is microdosing: taking psychedelics in very low doses. Here, however, the evidence is even sparser. We currently see no reason to think this will have benefits comparable to those of higher-dose psychedelic-assisted mental health treatments, as there is reason to believe that with classic psychedelics, the latter benefits are mediated by ‘mystical-type’ experiences, which microdosing doesn’t occasion. Furthermore, we don’t know much yet about the risks of prolonged microdosing, and from a legal perspective, making microdosing available for healthy people seems much further away than psychedelic-assisted mental health treatments.

I think the last point, about microdosing being further away than mental health treatments, applies to many flow-through effects. If, indeed, psychedelics could bring about wide-ranging benefits, then the best first step is probably to get them approved as mental health treatments anyway and so advancing this seems valuable. If approved, it will also be easier to carry out other kinds of research.

2. Did you consider more organisations than Usona and MAPS? It seems a little bit unlikely that these are the only two organisations lobbying for drug approval?

This is related to your other comment, so I’ll answer both together.

I was confused about the usage of the term drug development as it sounds to me like it’s about the discovery/​creation of new drugs, which clearly does not seem to be the high-value aspect here.

Drug development can but need not involve the creation of new drugs. It’s the process that has to happen in order for banned or new substances to be approved for medical use. It involves high-quality studies to prove efficacy and safety. Drug development is very expensive—it costs at least tens of millions of dollars (usually more) to go through the FDA approval process. So actually, there just aren’t many organisations able to do this. Usona and MAPS aren’t just lobbying for approval, they’re conducting clinical research in order to approve psilocybin and MDMA for medical use.

Another org also doing drug development of psilocybin (but for treatment-resistant depression, rather than major depression) is Compass Pathways. Compass is for-profit though, so we didn’t consider it as a funding opportunity here.

# Founders Pledge Re­port: Psychedelic-As­sisted Men­tal Health Treatments

30 Sep 2020 13:28 UTC
59 points
18 comments4 min readEA link
(founderspledge.com)

# Com­ments on “Us­ing Sub­jec­tive Well-Be­ing to Es­ti­mate the Mo­ral Weights of Avert­ing Deaths and Re­duc­ing Poverty”

29 Sep 2020 19:36 UTC
33 points
10 comments12 min readEA link
• I don’t think Greaves’ example suffers the same problem actually—if we truly don’t know anything about what the possible colours are (just that each book has one colour), then there’s no reason to prefer {red, yellow, blue, other} over {red, yellow, blue, green, other}.

In the case of truly having no information, I think it makes sense to use Jeffreys prior in the box factory case because that’s invariant to reparametrisation, so it doesn’t matter whether the problem is framed in terms of length, area, volume, or some other parameterisation. I’m not sure what that actually looks like in this case though

• yeah, these aren’t great examples because there’s a choice of partition which is better than the others—thanks for pointing this out. The problem is more salient if instead, you suppose that you have no information about how many different coloured marbles there are and ask what the probability of picking a blue marble is. There are different ways of partitioning the possibilities but no obviously privileged partition. This is how Hilary Greaves frames it here.

Another good example is van Fraassen’s cube factory, e.g. described here.